Retrieve a drink inventory summary with counts, brands, variants, and remaining milliliters per bottle and category, optionally filtered by beverage, brand, or category.
Return counts, brands, variants and remaining ml per bottle and category.
| Name | Required | Description | Default |
|---|---|---|---|
| brand | No | ||
| category | No | ||
| beverage_name | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It does communicate that the tool returns summarized inventory data and implies a read-only operation, but it does not explain aggregation behavior, filter semantics, or what happens when no filters are supplied.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the action and output contents. It is appropriately brief, though it is so terse that important behavioral and parameter context is omitted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With three optional parameters, no output schema, no annotations, and several sibling tools, the description is too incomplete. It does not explain how filters combine, whether results are aggregated globally or per filter, or when this tool should be preferred over list_inventory.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention any of the three optional parameters (brand, category, beverage_name) or how they affect the returned summary. The description provides no added meaning beyond the parameter names themselves.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear action ('Return counts, brands, variants and remaining ml') and identifies the tool as an inventory summary, distinguishing it somewhat from the sibling list_inventory by emphasizing summary-level aggregation. However, it does not explicitly contrast itself with siblings, so it is not fully differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus list_inventory or other inventory tools. The description implies it provides a summary, but it does not state when to choose it over alternatives or how filters should be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.